326 citations · 600 across the 23 of their papers we have counts for
4 papers · 1 filter
Enhanced Membership Inference Attacks against Machine Learning Models
Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda +2
How much does a machine learning algorithm leak about its training data, and why? Membership inference attacks are used as an auditing tool to quantify this leakage. In this paper,…
Beyond clipping: Equalization-based Psychoacoustic Attacks against ASRs
Hadi Abdullah, Muhammad Sajidur Rahman, Christian Peeters +5
Automatic Speech Recognition (ASR) systems convert speech into text and can be placed into two broad categories: traditional and fully end-to-end. Both types have been shown to be…
Leveraging Generative Models for Covert Messaging: Challenges and Tradeoffs for "Dead-Drop" Deployments
Luke A. Bauer, James K. Howes, Sam A. Markelon +2
State of the art generative models of human-produced content are the focus of many recent papers that explore their use for steganographic communication. In particular, generative…
Generative Models for Security: Attacks, Defenses, and Opportunities
Luke A. Bauer, Vincent Bindschaedler
Generative models learn the distribution of data from a sample dataset and can then generate new data instances. Recent advances in deep learning has brought forth improvements in…